Table of Contents
Algorithms, Volume 12, Issue 2 (February 2019)
- Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
- You may sign up for e-mail alerts to receive table of contents of newly released issues.
- PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Cover Story (view full-size image) Developments in embedded computing and machine learning can help build advanced wearable devices [...] Read more. Developments in embedded computing and machine learning can help build advanced wearable devices that provide accurate, on-the-spot diagnosis promising to complement traditional treatment and help patients self-manage their health condition. Utilizing recent technological developments in asymmetric multicore embedded processors, the wearable device locally analyzes the collected signal, accurately detects heartbeats, and classifies arrhythmia without any dependence on cloud services. The performance evaluation indicates that the achieved accuracy is high enough to conduct a first-level analysis of the signal in order to identify normal signals that do not need to be stored or transmitted to the cloud services. As a result, the proposed solution conserves bandwidth, limits the need for storage, and decreases latency. These findings are a positive indication that the fog-computing approach can indeed help address the problems resulting from an excess volume of data that are transferred f